Resampling multiple-site dissimilarity for n sites

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Description

Resamples the 3 multiple-site dissimilarities (turnover, nestedness-resultant fraction, and overall beta diversity) for a subset of sites of the original data frame.

Usage

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beta.sample(x, index.family="sorensen", sites=10, samples=100)

Arguments

x

data frame, where rows are sites and columns are species

index.family

family of dissimilarity indices, partial match of "sorensen" or "jaccard".

sites

number of sites for which multiple-site dissimilarities will be computed. If not specified, default is all sites.

samples

number of repetitions. If not specified, default is 1.

Value

The function returns a list with a dataframe with the resampled 3 multiple-site dissimilarities (turnover fraction, nestedness-resultant fraction and overall dissimilarity; see beta.multi), a vector with the respective means and a vector with the respective standard deviation.

For index.family="sorensen":

sampled.values

dataframe containing beta.SIM, beta.SNE and beta.SOR for all samples

mean.values

vector containing the mean values of beta.SIM, beta.SNE and beta.SOR among samples

sd.values

vector containing the sd values of beta.SIM, beta.SNE and beta.SOR among samples

For index.family="jaccard":

sampled.values

dataframe containing beta.JTU, beta.JNE and beta.JAC for all samples

mean.values

vector containing the mean values of beta.JTU, beta.JNE and beta.JAC among samples

sd.values

vector containing the sd values of beta.JTU, beta.JNE and beta.JAC among samples

Author(s)

Andrés Baselga and David Orme

References

Baselga, A. 2010. Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography 19:134-143

Baselga, A. 2012. The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Global Ecology and Biogeography 21, 1223-1232

See Also

beta.multi, beta.sample, beta.temp

Examples

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# Read the data for Northern and Southern European cerambycids
data(ceram.s)
data(ceram.n)

# Resample 100 times the multiple-site dissimilarities
# for 10 countries.
beta.ceram.s<-beta.sample(ceram.s, index.family="sor", sites=10, samples=100)
beta.ceram.n<-beta.sample(ceram.n, index.family="sor", sites=10, samples=100)

# Plot the distributions of beta.SIM in Southern Europe (red) 
# and Northern Europe (blue)
plot(density(beta.ceram.s$sampled.values$beta.SIM), col="red", xlim=c(0,1))
lines(density(beta.ceram.n$sampled.values$beta.SIM), col="blue")

# Compute the p-value of difference in beta.SIM between South and North 
# (i.e. the probability of finding in the North a higher value than 
# in the South)
p.value.beta.SIM<-length(which(beta.ceram.s$sampled.values$beta.SIM<
beta.ceram.n$sampled.values$beta.SIM))/100

p.value.beta.SIM
# The result is 0 and we used 100 samples, so p<0.01